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Project III
Nguyễn Việt Hoàng - 20194434

• Real-time Intrusion Detection System implementing Machine Learning.

• We combine Supervised learning (RF) for detecting known attacks from CICIDS 2018 & SCVIC-APT datasets, and Unsupervised Learning (AE) for anomaly detection.

• System descriptive diagram:

1. Windows OS.

2. Python 3.9:

   • link 64-bit:https://www.python.org/ftp/python/3.9.13/python-3.9.13-amd64.exe
   • link 32-bit:https://www.python.org/ftp/python/3.9.13/python-3.9.13.exe

   Note: select "Add Python 3.9 to PATH" in installation procedure.

3. Npcap 1.71:https://npcap.com/dist/npcap-1.71.exe

git clonehttps://github.com/HoangNV2001/APT_Detectioncd APT_Detection# Create a virtual environmentpython3.9 -m venv venv# Activate that virtual environmentsource venv/bin/activate# Install the project requirements.python -m pip install -r requirements.txt# or: pip install -r requirements.txt

Run program:

python application.py

Web app address:http://localhost:5000

• Main page, overview of real-time captured flows:

• Flow detail page: